The marriage of Renyi entropy with Parzen density estimation has been shown to be a viable tool in learning discriminative feature transforms.
Abstract. The marriage of Renyi entropy with Parzen density estimation has been shown to be a viable tool in learning discriminative feature transforms.
The marriage of Renyi entropy with Parzen density estimation has been shown to be a viable tool in learning discriminative feature transforms.
Learning Discriminative Feature Transforms to Low Dimensions in Low Dimentions. Open in new window. Thumbnails Document Outline Attachments
Supervised discriminative dimensionality reduction by ...
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SDR methods mainly try to learn one single transformation to project data into a low-dimensional subspace based on the provided labels information so that the ...
In this paper, we present a method to learn a set of discriminative tri-value patterns for projecting high dimensional raw visual inputs into a low dimensional ...
Sep 1, 2017 · It is achieved through introducing two types of labels and updating parameters by adaptively changed learning rate. This is different from the ...
Dec 5, 2021 · We introduce a new classifier for small-sample image data based on a two-dimensional discriminative regression approach.
In this study, we used unsupervised learning to discover the top-k discriminative features present in the large multivariate IoT dataset used.
Our approach circumvents this difficulty by learning a low-dimensional transformation of the φk's in a discriminative manner instead. Indeed, transforming ...